AI LEAD

Job Description

Greeting from Linnk Group Title: AI Lead - Generative AI & Deployment Location: Infopark, Kochi, Kerala Employment Type: Permanent About Us: Linnk Group is a global STEM recruitment and technology consultancy with established entities in the UAE, KSA, Qatar, India, and the UK. We are building AI-first platforms that power intelligent automation across recruitment, sales, and workforce management. Our technology stack includes LLM-based applications, RAG pipelines, CV parsing engines, chatbots, and agentic AI workflows integrated with cloud-native infrastructure. We are looking for a hands-on and experienced Lead AI/ML Engineer to architect, build, and scale our GenAI systems across products. This is a foundational role that will help define the technical direction and lead the implementation of production-grade AI components. Strong proficiency in deep learning and machine learning architectures, including ResNets, AlexNet, DenseNets, RCNNs, Vision Transformers (ViT) , Diffusion Models , and GANs In-depth understanding of Transformers and modern LLM architectures (e.g., LLaMA , Mistral , Qwen , GPT , Claude , BERT ), with a focus on NLP and generative AI . Familiarity with legacy models like RNNs and LSTMs is a plus. Expertise in Machine Learning (ML) and Natural Language Processing (NLP) frameworks such as PyTorch, Tensorflow, Hugging Face Transformers, LangChain . Proven experience designing recommendation systems and LLM-based applications , including RAG pipelines , structured generation, and retrieval systems. Skilled in model performance optimization , including quantization, pruning, latency reduction, and memory-efficient inference. Advanced knowledge of embeddings and vector search using tools like FAISS, Milvus, Pinecone, and Quadrant . Hands-on experience with CI/CD pipelines for ML/LLM workflows (e.g., GitHub Actions, Jenkins). In-depth understanding of MLOps and LLMOps practices including model versioning, deployment automation, drift detection, and continuous monitoring. Familiarity with automated evaluation frameworks. Skilled in Docker, Kubernetes , and building scalable microservices. Demonstrated experience deploying and maintaining ML systems on AWS , including SageMaker, EC2, EKS, RDS, and S3 . Ability to optimize and scale LLM inference endpoints , and orchestrate multi-agent workflows in production environments. Deep understanding of vector databases , semantic search , and dense retrieval techniques for real-time matching. Experience integrating with AI agent frameworks like LangGraph, Haystack, and CrewAI , and building robust RAG pipe